In this study, some mathematical relations have been derived for the useful parameters of fixed window functions in fractional Fourier transform (FRFT) domain. These reported expressions are also verified with the simulation studies. The FRFT provides an important extension to conventional Fourier transform with an additional degree of freedom by which these parameters of window functions can be controlled while inherent time domain behavior of the windows remains intact. The behavior of fixed windows on time-frequency plane has been varied by varying the FRFT order. The obtained variability in the window functions has been applied in the designing of FIR filters.

We define in this paper an extended solution to improve an Out-of-Core data structure which is the streaming format, by adding new information allowing to reduce file access cost, reducing the neighborhood access delay to constant time.
The original streaming format is conceived to manipulate huge triangular meshes. It assumes that the whole mesh cannot be loaded entirely into the main memory. That's why the authors did not include the neighborhood in the file structure.
However, almost all of the applications need the neighborhood information in the triangular structures. Using the original streaming format does not allow us to extract the neighborhood information easily. By adding the neighbor indices to the file in the same way as the original format, we can benefit from the streaming format, and at the same time, guarantee a constant time access to the neighborhood.
We have adapted our new structure so that it can allow us to apply our direct access algorithm to different parts of the structure without having to go through the entire file.

Segmenting tumor from MRI images is an essential but time consuming manual duty. Performing an automatic segmentation is a defying task since different forms of tumor tissue exist for diverse patients and in many cases the tumor is similar to the normal tissue. Various studies proposed earlier to handle the issue of precisely segmenting the tumor but they discard the degradations and their effect to the precision of the segmentation. This article provides a more precise segmentation process through the use of appropriate pre-processing algorithms. The authors studied many enhancement and restoration algorithms and selected the NL-means, Laplacian filter and histogram equalization to be used as preprocessing techniques. Experimental results showed that using a suitable preprocessing scheme would produce a better segmentation process.

This paper shows a symmetric image encryption based on bit-wise operation (XORing and Shifting). The basic idea is block ciphering (size of each block is 4 bytes) technique to cipher the secret bytes, after that ciphered bytes are again shuffled among N positions (N is the size of secret file). The scheme is combination of substitution as well as transposition techniques which provides additional protection of the secret data. The substitution and transposition are done using dynamic substitution box (SBOX) and transposition box (TBOX) which are generated using the secret key and made to vary for each block during ciphering. The size of encrypted data is same as the size of secret data and the proposed scheme has been tested using different images. We have also presented the security analysis such as key sensitivity analysis, statistical analysis, and differential analysis to prove the strength of our algorithm against crypto analysis.

The paper presents an intelligent multi gesture spotting system that can be used by disabled people to easily communicate with machines resulting into easement in day-to-day works. The system makes use of pose estimation for 10 signs used by hearing impaired people to communicate. Pose is extracted on the basis of silhouettes using timed motion history (tMHI) followed by gesture recognition with Hu-Moments. Signs involving motion are recognized with the help of optical flow. Based on the recognized gestures, particular instructions are sent to the robot connected to system resulting into an appropriate action/movement by the robot. The system is unique as it can act as a assisting device and can communicate in local as well as wide area to assist the disabled person.

In biometric systems, reference threshold is defined as a value that can decide the authenticity of a person. Authenticity means whether the person is genuine or intruder. The statistical calculation of various values like reference threshold, FAR (False Acceptance Rate), FRR (False Rejection Rate) are required for real-time automated biometric authentication system because the measurement of biometric features are statistical values. In this paper, the need of reference threshold, how reference threshold value is calculated is explained mathematically. Various factors on which reference threshold value depends are discussed. It is also explained that how selection of correct value of reference threshold plays an important role in authentication system. Experimental results describe the selection of reference threshold value for palmprint biometric system.

A vital problem in evaluating the picture quality of an image compression system is the difficulty in describing the amount of degradation in reconstructed image, Wavelet transforms are set of mathematical functions that have established their viability in image compression applications owing to the computational simplicity that comes in the form of filter bank implementation. The choice of wavelet family depends on the application and the content of image. Proposed work is carried out by the application of different hand designed wavelet families like Haar, Daubechies, Biorthogonal, Coiflets and Symlets etc on a variety of bench mark images. Selected benchmark images of choice are decomposed twice using appropriate family of wavelets to produce the approximation and detail coefficients. The highly accurate approximation coefficients so produced are further quantized and later Huffman encoded to eliminate the psychovisual and coding redundancies. However the less accurate detailed coefficients are neglected. In this paper the relative merits of different Wavelet transform techniques are evaluated using objective fidelity measures- PSNR and MSE, results obtained provide a basis for application developers to choose the right family of wavelet for image compression matching their application.

Automatic recognition of facial expressions can be an important component of natural human-machine interfaces; it may also be used in behavioural science and in clinical practice. Although humans recognise facial expressions virtually without effort or delay, reliable expression recognition by machine is still a challenge. This paper, presents recognition of facial expression by integrating the features derived from Grey Level Co-occurrence Matrix (GLCM) with a new structural approach derived from distinct LBP’s (DLBP) ona 3 x 3 First order Compressed Image (FCI). The proposed method precisely recognizes the 7 categories of expressions i.e.: neutral, happiness, sadness, surprise, anger, disgust and fear. The proposed method contains three phases. In the first phase each 5 x 5 sub image is compressed into a 3 x 3 sub image. The second phase derives two distinct LBP’s (DLBP) using the Triangular patterns between the upper and lower parts of the 3 x 3 sub image. In the third phase GLCM is constructed based on the DLBP’s and feature parameters are evaluated for precise facial expression recognition. The derived DLBP is effective because it integrated with GLCM and provides better classification performance. The proposed method overcomes the disadvantages of statistical and formal LBP methods in estimating the facial expressions. The experimental results demonstrate the effectiveness of the proposed method on facial expression recognition.